Travel pattern generation device, vehicle, and travel pattern generation method

Abstract

To provide a travel pattern generation device, a vehicle, and a travel pattern generation method, capable of ensuring high safety and regularity and even margin time.SOLUTION: A travel pattern generation device comprises: a danger-degree evaluation and countermeasure examination unit that calculates, for each of detection performance information representing detection performance for an obstacle, a section characteristic map representing a type of a travel section and characteristics of a surrounding object, standard speed limit information, vehicle position information, standard driving curve information, and a plurality of countermeasure candidates defined by the standard speed limit information or the detection performance information, a danger degree which is an index taking into consideration the occurrence frequency and the damage degree of both or one of a human damage and a vehicle damage at the time of collision in a travel section using the section characteristic map and the countermeasure candidates for each travel section and margin time, selects a countermeasure on the basis of the danger degree and the margin time, and calculates a countermeasure speed limit; and a travel pattern generation unit that calculates a travel pattern up to a next station on the basis of countermeasure speed limit information regarding the countermeasure speed limit, the standard driving curve information, and the vehicle position information.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a drive pattern generation device, a vehicle, and a drive pattern generation method, and is suitable for application to, for example, a drive pattern generation device and a vehicle that generate a vehicle drive pattern that can ensure safety while also ensuring margin of error. [Background technology]

[0002] Unmanned driving has been attracting attention as a way to reduce costs in the rail transport business. Unmanned driving systems have been put to practical use in new transportation systems that are isolated from the outside environment, but in recent years, there have been considerations of introducing them to railway systems that cross paths with other forms of traffic, such as automobiles and pedestrians. However, since such railway systems allow objects that impede vehicle travel (hereafter referred to as "obstacles") to easily enter the roadway, technology is needed to avoid collisions with obstacles or reduce the damage caused by collisions. In response to this, development is being carried out on technology to detect obstacles using on-board external sensors, and studies are being conducted on generating driving patterns with the aim of improving the safety of unmanned driving of vehicles equipped with external sensors.

[0003] An unmanned vehicle equipped with an external sensor is required to decelerate as soon as it detects an obstacle in front of the vehicle, to avoid a collision with the obstacle, or to reduce the damage caused by the collision. In such a railway system, if the vehicle travels at a speed that exceeds the obstacle detection capability of the external sensor, for example, at a speed that exceeds the detectable distance, even if an obstacle is found in front of the vehicle while traveling, the vehicle cannot brake in time, making it difficult to avoid a collision with the obstacle. Therefore, it is important to generate a traveling pattern that takes into account the obstacle detection capability of the external sensor. On the other hand, compliance with the railway timetable is also necessary to maintain railway service, and the following Patent Documents 1 and 2 disclose technologies that take into account the obstacle detection capability and the punctuality of the railway timetable.

[0004] Patent Document 1 discloses a technology that takes into account risks such as collisions with obstacles, maintains a risk value for each section and a running time specified in a timetable, and generates a running pattern that satisfies specified conditions according to the running time and minimizes the risk impact, thereby reducing the risk of collisions between a rail transport system and obstacles while meeting running times between stations.

[0005] Patent document 2 discloses a technology in which a restriction pattern is created based on the detectable distance of an obstacle in front of the vehicle, an initial pattern is created based on this restriction pattern, and if the initial pattern cannot meet the travel time between stations, a modified pattern obtained by modifying the initial pattern so that the travel time is within a specified time, is used to calculate a travel pattern. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Patent No. 7164306 [Patent Document 2] JP 2023-37434 A Summary of the Invention [Problem to be solved by the invention]

[0007] The technology disclosed in Patent Document 1, as described above, makes it possible to reduce the risk of collision between the rail transportation system and obstacles while enabling trains to run according to a schedule based on the risk associated with the frequency of obstacle appearances. However, no consideration is given to how to ensure slack time at appropriate positions while ensuring high safety and punctuality in light of the risk value for each section.

[0008] In addition, in the technology disclosed in Patent Document 2, as described above, a driving pattern is calculated using a modified pattern obtained by modifying an initial pattern so that the driving time is within a specified time, but no consideration is given to ensuring a slack time while ensuring high safety and punctuality by taking into account the frequency and damage of dangerous events.

[0009] The present invention has been made in consideration of the above points, and aims to propose a driving pattern generation device, a vehicle, and a driving pattern generation method that can not only ensure high safety and punctuality, but also ensure slack time. [Means for solving the problem]

[0010] In order to solve such problems, the present invention provides a risk assessment and countermeasures consideration unit that uses the section characteristics map and the countermeasure candidates to determine, for each of a plurality of countermeasure candidate options defined by the standard speed limit information or the detection performance information, a risk assessment and countermeasures consideration unit that uses the section characteristics map and the countermeasure candidates to determine a risk level and a margin of error, which are indexes taking into account the frequency of occurrence and degree of damage to persons and / or vehicles in the event of a collision in the traveling section, and calculates a countermeasure speed limit corresponding to the countermeasure, and a travel pattern generation unit that calculates a travel pattern to the next station based on the countermeasure speed limit information related to the countermeasure speed limit, the standard travel curve information, and the vehicle position information.

[0011] In addition, in the present invention, the risk assessment and countermeasure consideration unit of the driving pattern generation device uses a section characteristic map representing the type of driving section and the characteristics of surrounding objects and the countermeasure candidates to determine a risk, which is an index taking into account the frequency of occurrence and the degree of damage to humans and / or vehicles in the event of a collision in the driving section, and a margin of error for each of a plurality of countermeasure candidates defined by standard speed limit information related to the standard speed limit when the vehicle travels, or detection performance information representing the detection performance of an obstacle, for each of the driving section, and selects a countermeasure from the countermeasure candidates based on the risk and the margin of error, and calculates a countermeasure speed limit corresponding to the countermeasure; and the driving pattern generation unit of the driving pattern generation device has a risk assessment and countermeasure consideration step of calculating a driving pattern to the next station based on the countermeasure speed limit information related to the countermeasure speed limit, standard driving curve information representing the driving mode set so that the vehicle adheres to the timetable, and vehicle position information representing the position of the vehicle. Effect of the Invention

[0012] According to the present invention, it is possible to realize a drive pattern generation device, a vehicle, and a drive pattern generation method that can ensure not only high safety and punctuality but also slack time. [Brief description of the drawings]

[0013] [Figure 1] 1 is a diagram illustrating an example of the configuration of a vehicle equipped with a drive pattern generation device according to a first embodiment. [Diagram 2] 4A to 4C are diagrams illustrating specific examples of section characteristic maps according to the first embodiment. [Diagram 3] FIG. 11 is a diagram illustrating a specific example of detection performance information. [Figure 4] FIG. 2 is a block diagram mainly showing an example of the functions of a risk assessment and countermeasures examination unit. [Diagram 5] FIG. 13 is a diagram showing a specific example of a risk matrix specific to a route. [Figure 6] FIG. 13 is a diagram showing a specific example of a standard risk matrix. [Figure 7] FIG. 13 is a diagram showing a specific example of frequency and importance. [Figure 8] FIG. 13 is a diagram showing a specific example of a method for calculating an S risk level. [Figure 9] FIG. 13 is a diagram showing a specific example of a risk calculation method. [Figure 10] FIG. 13 is a diagram showing a specific example of a countermeasure candidate matrix. [Figure 11] FIG. 13 is a diagram showing a specific example of a post-measures consideration matrix. [Figure 12] FIG. 13 is a diagram showing a specific example of a countermeasure integration matrix. [Figure 13] 10A to 10C are diagrams showing specific examples of vehicle positions where each countermeasure is implemented. [Figure 14] FIG. 11 is a diagram showing a specific example of countermeasure speed limit information. [Figure 15] This is a schematic diagram showing the section characteristics and lineside characteristics divided by countermeasure sections, and a diagram visualizing the countermeasure speed limit at each point and the driving pattern calculated based on the countermeasure speed limit. [Figure 16] FIG. 11 is a diagram illustrating an example of a method for correcting a driving pattern. [Figure 17] FIG. 11 is a diagram illustrating an example of the configuration of a vehicle equipped with a drive pattern generation device according to a second embodiment. [Figure 18] This is a schematic diagram showing the section characteristics and lineside characteristics divided by countermeasure sections, and a diagram visualizing the countermeasure speed limit at each point and the driving pattern calculated based on the countermeasure speed limit. [Figure 19] FIG. 11 is a diagram illustrating an example of the configuration of a vehicle including a risk assessment and countermeasures consideration unit of a drive-pattern generation device according to a third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] An embodiment of the present invention will now be described in detail with reference to the drawings.

[0015] (1) First embodiment 1 is a diagram showing a configuration example of a vehicle 1 equipped with a driving pattern generation device 2 in the first embodiment. In the illustrated example, the driving pattern generation device 2 is provided in the vehicle 1, but the driving pattern generation device 2 may be mounted in a location other than the vehicle 1, for example, on ground equipment.

[0016] The vehicle 1 is a vehicle that runs based on a predetermined running plan, such as a railway. A running plan for a railway is a running pattern, and this running pattern indicates information that summarizes the control speed of the vehicle 1 for each running position based on the vehicle's position, the target running time to the next station, the speed limit, etc.

[0017] The driving pattern generation device 2 includes a section characteristic map 21, standard speed limit information 22, detection performance information 23, a risk assessment and countermeasures consideration unit 24, countermeasure speed limit information 25, standard driving curve information 26, vehicle position information 27 and a driving pattern generation unit 28, and preferably further includes a detection performance calculation unit 29 and a driving pattern correction unit 210.

[0018] The obstacle detection sensor 3 is provided, for example, on the front of the vehicle 1, and outputs a forward object detection result that detects an obstacle (hereinafter also referred to as "object") in front of the vehicle 1, and outputs a forward rail detection result that detects a rail in front of the vehicle 1. The obstacle detection sensor 3 is connected to the detection performance calculation unit 29 of the driving pattern generation device 2, and outputs the forward object detection result and the forward rail detection result (hereinafter both are collectively referred to as "forward information") to the detection performance calculation unit 29. The obstacle detection sensor 3 is mounted on the vehicle 1 as described above, and has a function of acquiring information including the object position in front of the vehicle. The obstacle detection sensor 3 is, for example, a camera, a laser radar, etc.

[0019] The section characteristic map 21 indicates the type of traveling section and the characteristics of surrounding objects. The section characteristic map 21 is map information that compiles the characteristics of the lineside and the presence or absence of obstacles for each traveling section. The standard speed limit information 22 is information on the standard speed limit that is predefined for each line. The section characteristic map 21 includes, for example, vehicle traveling position, traveling section characteristics, and collision scenes with obstacles that are expected for each lineside characteristics.

[0020] The standard speed limit information 22 indicates the upper speed limit of the vehicle 1 that is defined in advance for the route on which the vehicle 1 travels, depending on the performance of the vehicle 1, the curvature of the travel section, branches, railroad crossings, and the like.

[0021] The detection performance information 23 represents the detection performance of the obstacle detection sensor 3. The detection performance information 23 is information representing the detection performance of the obstacle detection sensor 3, in which the maximum distance at which the obstacle detection sensor 3 can detect an obstacle is recorded as the detection distance for each traveling position of the vehicle 1.

[0022] The risk assessment and countermeasures consideration unit 24 uses the section characteristic map 21 and the countermeasure candidates for each of a plurality of countermeasure candidates defined by the standard speed limit information 22 or the detection performance information 23 to determine the risk, which is an index taking into account the frequency of occurrence and the degree of damage to persons and / or vehicles in the event of a collision in the traveling section, and the margin time, and selects a countermeasure from the countermeasure candidates based on the risk and margin time, and calculates the countermeasure speed limit corresponding to the countermeasure.

[0023] The risk assessment and countermeasures consideration unit 24 calculates an appropriate countermeasure speed limit taking into consideration the risk and margin time using the standard speed limit information 22 and the detection performance information 23, and obtains countermeasure speed limit information 25 relating to the countermeasure speed limit.

[0024] The risk assessment and countermeasures consideration unit 24 uses the section characteristics map 21, standard speed limit information 22 predefined for each route, and detection performance information 23 to calculate countermeasure speed limit information 25 that indicates an appropriate countermeasure speed limit from multiple speed limit candidates, taking into account the risk and margin of error.

[0025] As an example of a countermeasure, the risk assessment and countermeasure consideration unit 24 selects at least one of a first countermeasure Level.1, which sets the speed limit at the smaller of a speed at which the vehicle can be stopped within a distance obtained by adding a first predetermined value to the obstacle detection distance detected by the obstacle detection sensor 3, or the standard speed limit, and a second countermeasure Level.2, which sets the speed limit at the smaller of a speed at which the vehicle can be stopped within a distance obtained by subtracting a second predetermined value from the detection distance, or the standard speed limit.

[0026] The risk assessment and countermeasure examination unit may select, as a countermeasure, countermeasure level 1, countermeasure level 2, or a third countermeasure level 3 in which the speed limit is set to the smaller of the speed at which the vehicle can stop within a distance obtained by subtracting a third predetermined value from the detection distance and the standard speed limit. The speed limit of the third countermeasure level 3 is equal to or lower than the speed limit of countermeasure level 2.

[0027] The travel pattern generation unit 28 calculates a travel pattern to the next station based on countermeasure speed limit information 25 related to the countermeasure speed limit, standard travel curve information 26, and vehicle position information 27. The standard travel curve information 26 is information representing the travel mode set for the vehicle 1 to keep to the timetable, and includes, for example, at least the target travel time between each station. The target travel time is the travel time between stations that needs to be observed in order to keep to the timetable. The vehicle position information 27 represents the current position of the vehicle 1, and is expressed, for example, by information using kilometers.

[0028] The detection performance calculation unit 29 uses the forward information output from the obstacle detection sensor 3 to calculate the current detection capability (of an obstacle) of the obstacle detection sensor 3, and obtains current detection performance information of the obstacle detection sensor 3. The detection performance calculation unit 29 calculates the current obstacle detection capability using the obstacle detection sensor 3. The obstacle detection capability is, for example, the maximum detection distance of an obstacle by the obstacle detection sensor 3. As a method for calculating the maximum detection distance, for example, a method can be adopted in which the obstacle detection sensor 3 uses the forward object detection result and the forward rail detection result of the vehicle 1 to extract an obstacle that may be an obstacle to traveling, and under the assumption that the detection distance of the obstacle is longer than the detection distance of the rail, the maximum detection distance of the obstacle is set to the maximum detection distance of the rail.

[0029] The driving pattern correction unit 210 corrects the above-mentioned driving pattern based on the vehicle position information 27, the detection performance information 23, and the current detection performance information calculated by the detection performance calculation unit 29. Specifically, the driving pattern correction unit 210 uses the current obstacle detection distance calculated by the detection performance calculation unit 29 and combines it with the detection performance information 23 to correct the detection distance used when calculating the speed limit for countermeasure Level 2 and countermeasure Level 3 sections as examples of multiple countermeasure candidates described later, and corrects the driving pattern generated by the driving pattern generation unit 28, taking into account the vehicle position information 27.

[0030] In this embodiment, the risk level is an index that takes into consideration the frequency of occurrence and the degree of damage to both human beings and vehicle damage, or either one, in the event of a collision. The risk level is expressed, for example, as any value from 1 to 3. The higher the frequency of occurrence or the greater the degree of damage, the higher the risk level "3".

[0031] In addition, in this embodiment, the term "S risk level" is used as an index that takes into account human damage and the frequency of collisions when a collision occurs, and the term "A risk level" is used as an index that takes into account vehicle damage and the frequency of collisions when a collision occurs. The risk level includes S risk level and A risk level. However, the risk level including S risk level and A risk level is just an example, and it may be either S risk level or A risk level.

[0032] Here, an outline of a driving pattern generation method will be described as an operation example of the driving pattern generation device 2. The driving pattern generation method includes a risk evaluation and countermeasure consideration step in which a risk evaluation and countermeasure consideration unit 24 of the driving pattern generation device 2 uses a section characteristic map representing the type of the driving section and the characteristics of the surrounding objects and the countermeasure candidates to obtain a risk, which is an index considering the occurrence frequency and damage degree of both human damage and vehicle damage at the time of a collision in the driving section, and a margin time for each of a plurality of countermeasure candidates defined by standard speed limit information 22 related to the standard speed limit when the vehicle travels or detection performance information representing the detection performance of an obstacle, and selects a countermeasure from the countermeasure candidates based on the risk and margin time, and calculates a countermeasure speed limit corresponding to the countermeasure; and a driving pattern generation step in which a driving pattern generation unit 28 of the driving pattern generation device 2 calculates a driving pattern to the next station based on countermeasure speed limit information related to the countermeasure speed limit, standard driving curve information representing the driving mode set so that the vehicle 1 follows the timetable, and vehicle position information representing the position of the vehicle. As will be described later, the driving pattern correction unit 210 corrects the driving pattern in consideration of the current detection performance of the obstacle detection sensor 3 obtained from the detection performance calculation unit 29 while the vehicle 1 is traveling.

[0033] 2 shows a specific example of a section characteristic map in this embodiment. Table T1 includes start mileage T11, end mileage T12, section characteristics T13, line characteristics T14, and station names T15.

[0034] The start kilometre T11 is the kilometre from the starting point, which represents the start position of the continuous facility. The end kilometre T12 is the kilometre from the starting point, which represents the end position of the continuous facility. The section characteristic T13 is information classified according to the likelihood of the appearance of an obstacle, and includes at least types such as station, crossing, depot, and none. The reason for providing the section characteristic T13 in this way is that, for example, while there is a risk of an object entering from the platform at a station, people do not normally enter between multiple stations, and therefore the purpose is to distinguish between these and estimate the frequency of object intrusion. The type "none" is a section that does not fall into a specific category such as a station, crossing, or depot, and does not include elements specific to a specific facility, consisting only of elements such as a track and an overhead pole.

[0035] The lineside characteristics T14 are information indicating whether or not there is a physical barrier to intrusion onto the track. The lineside characteristics T14 include the presence or absence of obstacles along the track and the topographical condition along the track. The obstacles include, for example, the presence or absence of fences and platform screen doors. The topography includes, for example, whether the topography is flat, hilly, or valley-like. If there is a fence, it is not easy for an object to intrude onto the track, and if the topography is hilly or valley-like, it is more difficult to intrude onto the track than if it is flat. For this reason, in this embodiment, these pieces of information are managed separately from each other.

[0036] The station name T15 is the name of the station at that kilometer distance. The kilometer distance is a vehicle position defined along the track from the starting station, and this embodiment is applied when the vehicle 1 moves from a specific station A to station B in a direction in which the kilometer distance increases, but it may also be applied when the vehicle 1 moves in a direction in which the kilometer distance decreases.

[0037] In other words, for example, looking at the second row (T16) of Table T1, for the section between 240 and 2000 meters in distance, the section characteristic T13 is “none,” and the line characteristic T14 indicates that there are no obstructions such as fences, and the terrain is flat.

[0038] 3 is a diagram showing a specific example of the detection performance information 23. The detection performance information 23 is shown by table T2, and includes a detection distance T23, a start kilometer T21 of the detection distance T23, and an end kilometer T22. For example, the first line T24 of table T2 indicates that the detection distance is 300 m in the kilometer range of 20 to 500 m.

[0039] Here, as a method for calculating the maximum detection distance in this embodiment, for example, a method can be adopted in which, on the premise that an obstacle that may be an obstacle to traveling is extracted using forward information acquired by the obstacle detection sensor 3, and the detection distance of the obstacle is longer than the detection distance of the rail, the maximum detection distance of the obstacle is set as the maximum detection distance of the rail. In this embodiment, the detection distance obtained by such a calculation method is managed as detection performance information 23.

[0040] As another method of calculating the maximum detection distance in this embodiment, the detection performance information 23 is defined in advance before the vehicle 1 begins driving operations. For example, during times outside of the vehicle 1's operating hours, the vehicle 1 is driven with a driver on board to obtain information indicating the detection performance of the obstacle detection sensor 3, and the maximum detection distance of an obstacle for each position of the vehicle 1 is calculated and used as information indicating the detection performance.

[0041] 4 is a block diagram mainly showing an example of the functions of the risk assessment and countermeasures examination unit 24. The risk assessment and countermeasures examination unit 24 has a risk matrix generation unit 241, a risk countermeasures examination unit 242, a risk countermeasures examination result integration unit 243, and a driving method map generation unit 244. The risk assessment and countermeasures examination unit 24 outputs speed limit information 245 that takes into account the balance between risk and margin time.

[0042] The risk matrix generation unit 241 uses the section characteristics map 21 to generate a risk matrix including risk for each traveling section based on the traveling section characteristics, line characteristics, vehicle threat level corresponding to anticipated obstacles, level of personal injury, and frequency of appearance of the obstacles.

[0043] Specifically, the risk matrix generation unit 241 extracts collision scenes with obstacles that are expected for each vehicle driving position, driving section characteristics, and line characteristics based on the section characteristics map 21, and calculates the risk of personal injury due to collision (S risk) and the risk related to reduced vehicle availability due to accidents (A risk) for each collision scene, and generates a risk matrix.

[0044] The risk countermeasure examining unit 242 uses the risk matrix, the detection performance information, and the standard speed limit information to generate a countermeasure candidate matrix that compiles information including at least the risk reevaluation result and the margin time when the countermeasure candidate is implemented.

[0045] Specifically, the risk countermeasures review unit 242 uses the risk matrix output by the risk matrix generation unit 241, the detection performance information 23, and the standard speed limit information 22 to generate a candidate countermeasures matrix that summarizes the risk reevaluation results (S risk level, A risk level) and margin time when each countermeasure related to the speed limit is implemented in each driving section.

[0046] The risk countermeasure review result integration unit 243 uses the result of selecting countermeasures from the countermeasure candidates based on the countermeasure candidate matrix to generate a countermeasure review post-review matrix that summarizes the countermeasure review results for each travel section. More specifically, the risk countermeasure review result integration unit 243 summarizes the countermeasure selection results for each scene for the countermeasure candidate matrix output by the risk countermeasure review unit 242 as a countermeasure review post-review matrix, and further generates a countermeasure integration matrix that summarizes the countermeasure selection results for each travel section based on the countermeasure review post-review matrix.

[0047] The driving method map generation unit 244 uses the post-countermeasure consideration matrix, the detection performance information 23, and the standard speed limit information 22 to output countermeasure speed limit information 25 regarding the countermeasure speed limit that may differ from the above-mentioned standard speed limit, based on the countermeasure start position and countermeasure end position of the countermeasure, and the speed limit at the time the countermeasure is implemented.

[0048] In this embodiment, the start point of the section where the measure to determine the speed limit based on the detection performance is taken is a predetermined distance before the start point of the running section characteristics and lineside characteristics corresponding to the section where the measure to determine the speed limit based on the detection performance is taken. The predetermined distance is the distance at which the train can stop at the speed limit used in the measure to determine the speed limit based on the detection performance.

[0049] The risk assessment and countermeasures consideration unit 24 selects, for each travel section, from among the candidate countermeasures, a countermeasure whose risk level meets a predetermined level and whose margin time is equal to or greater than a predetermined value.

[0050] As described above, the driving pattern generation device 2 includes the detection performance calculation unit 29 and the driving pattern correction unit 210. The detection performance calculation unit 29 calculates the current detection performance of the obstacle detection sensor 3 that detects an obstacle or a rail in front of the vehicle 1. The driving pattern correction unit 210 obtains an estimation result of the detection performance in the section along which the vehicle travels based on the current detection performance based on the current detection performance, and corrects the driving pattern output by the driving pattern generation unit 28 based on the estimation result of the detection performance and the vehicle position information 27.

[0051] In this embodiment, the driving pattern correction unit 210 sets an estimated section prior to the section along which travel is to be made based on the current detection performance in order to estimate the current detection capability (of obstacles) of the obstacle detection sensor 3, and sets, as the end position of the estimated section, a position at which, if the detection performance expected in the section along which travel is to be made based on the detection performance deteriorates at the start point of the section along which travel is to be made based on the current detection performance, deceleration is started from the end position of the estimated section, and deceleration can be started up to the speed limit corresponding to the deteriorated detection performance by the start point of the section along which travel is to be made based on the current detection performance.

[0052] The driving pattern correction unit 210 calculates a deterioration coefficient by dividing a first detection distance, which is the detection capability of the obstacle detection sensor 3 at the current position, by a second detection distance, which is the detection capability of the obstacle detection sensor 3 acquired in the past at the same location, and obtains an estimated result of the detection performance of the obstacle detection sensor 3 by multiplying the detection distance of the section being driven by the deterioration coefficient based on the detection performance defined in advance.

[0053] Fig. 5 shows a specific example of a route-specific risk matrix. Fig. 6 shows a specific example of a standard risk matrix. Fig. 7 shows a specific example of frequency and importance. Fig. 8 shows a specific example of the S risk calculation method, and Fig. 9 shows a specific example of the A risk calculation method.

[0054] First, the risk matrix shown in Figure 5 includes kilometres T31 corresponding to section characteristics T32 and lineside characteristics T33, obstacles T34 expected in the section characteristics T32 and lineside characteristics T33, obstacle collision scenes (hereinafter also simply referred to as "scenes") T35, and S risk and A risk as risk evaluation results in the S risk calculation T36 and the A risk calculation T37.

[0055] The kilometre distance T31, section characteristics T32 and lineside characteristics T33 are set using the section characteristics map 21 described above, and the obstacles T34 and scenes T35 are set taking into consideration the section characteristics T32 and lineside characteristics T33.

[0056] For example, for row T39, since there is a possibility of a person entering the station premises, a person is selected as the obstacle T34, and for scene T35, a pedestrian enters the track and collides. If there is a possibility of multiple obstacles, such as pedestrians and cars, entering between stations, as in rows T310 and T311, separate rows are set, and a scene T35 is set for each obstacle T34.

[0057] Also, when there is an obstruction (e.g., a bicycle) as in line T314, scene T35 is set taking the obstruction into consideration. The same goes for the terrain; when the terrain is not flat but hilly, for example, a scene such as "a pedestrian climbs a hill, enters the track, and collides with a vehicle" is set. In this way, scene T35 is set taking into consideration section characteristics T32, lineside characteristics T33, and obstacles T34, which helps to more specifically consider the frequency of occurrence of scene T35 and human and vehicle damage in the event of a collision.

[0058] In the S risk calculation T36, the S risk is calculated based on the degree of human damage in the event of a collision and the frequency of collisions. In this embodiment, the risk is evaluated in the order of worsening, "◎", "○", "△", and "×". A poor S risk evaluation result indicates that human damage is great. The S risk is calculated based on the occurrence frequency and importance of the scene T35.

[0059] In this embodiment, frequency is divided into six levels, A to F, and importance is divided into four levels, 1 to 4. For each scene, the frequency is determined, for example, from Table T51 in FIG. 7, and the importance level is determined from Table T52, and then the S risk level is calculated from Table T53 in FIG.

[0060] Table T51 in Fig. 7 is a specific example of indexes of the frequency of occurrence of a scene, with the frequency of occurrence of a scene decreasing from A to F. In this embodiment, the frequency is defined as the occurrence probability in one hour [ / h], but other quantitative indexes may be used. In this embodiment, the frequency is defined as six stages as an example, but six stages is not essential.

[0061] Table T52 in Fig. 7 is a specific example of an index of the degree (importance) of human damage when a scene occurs, with the degree of human damage increasing from 1 to 4. Table T52 is an example for expressing the degree of human damage, and the four stages shown in the figure are not essential.

[0062] Table T53 in Fig. 8 is a table for calculating the S risk level based on the evaluation results of frequency and importance. For example, for a certain scene, if the frequency is A and the importance is 2, the S risk level is "x", and if the frequency is C and the importance is 4, the S risk level is "o".

[0063] The legend for the symbols for S risk level is shown in Table T54 in Figure 8. "X" indicates a scene that is unacceptable from the perspective of human damage and therefore requires some kind of countermeasure. "△" indicates a scene where the necessary measures for improvement are not realistic and in some cases are acceptable with the operator's consent. "○" indicates a scene that is acceptable if the necessary measures are taken and the operator's consent is obtained, and "◎" indicates a scene that is acceptable even without the operator's consent.

[0064] In the A risk calculation T37, the A risk is calculated based on the degree of damage to the vehicle 1 at the time of collision and the frequency of collisions. When the A risk is poor (the order of evaluation is worse: "◎", "○", "△", and "×"), it indicates that the vehicle recovery after the scene occurs is slow and the vehicle operation rate is greatly reduced. The A risk is calculated based on the frequency and threat of the scene. The frequency is set to the above-mentioned six levels of A to F, and the threat level is set to three levels of 1 to 3. For each scene, the frequency is determined, for example, by Table T51 in FIG. 7, and the threat level is determined by Table T61 in FIG. 9, and the A risk is further calculated by Table T61.

[0065] Table T61 in Fig. 9 is a specific example that summarizes the index of the degree of vehicle damage (threat level) when a scene occurs. As the threat level increases from 1 to 3, the vehicle damage becomes minor, and even if the vehicle is damaged, it will be quickly restored. Table T61 is also an example for expressing vehicle damage, and it is not necessary to have three levels.

[0066] Table T62 in Fig. 9 is a table for calculating the A-risk level based on the evaluation results of the frequency and the threat level. For example, for a certain scene, if the frequency is A and the threat level is 2, the A-risk level is "x", and if the frequency is C and the threat level is 3, the A-risk level is "o".

[0067] The legend for risk level A is shown in Table T63 in Figure 9. "X" indicates a scene where some kind of countermeasure is essential because the damage to the vehicle is large and it will take time to restore the vehicle. "△" indicates a scene where the necessary measures for improvement are not realistic and in some cases are acceptable if the operator agrees. "○" indicates a scene that is acceptable if the necessary measures are taken and the operator agrees, and "◎" indicates a scene that is acceptable even without the operator's agreement.

[0068] Furthermore, Table T3 is created for each target route, but in this embodiment, when creating Table T3, a standard risk matrix is ​​created in advance that summarizes various section characteristics, line characteristics, collision scenes corresponding to obstacles, and even S risk levels and A risk levels, and when creating the risk matrix for the target route, those that match the section characteristics and line characteristics of the target route are extracted from the standard risk matrix, and this can be used as a route-specific risk matrix.

[0069] In Table T4 in the standard risk matrix shown in Figure 6, instead of information about mileage, IDs (T41) defined for each section characteristic (T42), lineside characteristic (T43), and obstacle (T44) are set. When creating a line-specific risk matrix, rows of Table T4 with IDs matching the section characteristics and lineside characteristics of the target line are extracted and used as the line-specific risk matrix.

[0070] A specific example of how to select the frequency, importance, and threat level for each scene will be explained. For row T39 in Table T3 mentioned above, the frequency index A indicates that it occurs 0.74 times per year, and it was determined that a person falling onto the tracks in a station occurs more than 0.74 years per year, so "index A" was selected for frequency. For importance, there is a possibility that a single fatal failure may occur, so "2" was selected. For threat level, "2" was selected because after an accident occurs, it will take about 1 to 2 hours to restore the system, although it will not require a replacement of the car.

[0071] For row T310 of Table T3, in terms of frequency, "E" was selected because a car would need to break through the wall surrounding the station to enter the station premises, which is an extremely low possibility. For importance, "1" was selected because there is a risk of the car derailing if a car collides with a rail car, and multiple fatal failures could occur. For threat level, "1" was selected because in the event of a derailment, recovery on the same day is unlikely, such as by replacing the car.

[0072] For row T311 in Table T3, if there is no barrier such as a fence on the track between stations, it is possible to enter the track. Therefore, the frequency is selected as "C", and the importance and threat are set to "2" as with T39.

[0073] For row T312 in Table T3, since there are no roads that cross the tracks between the stations, the possibility of intrusion onto the tracks is extremely low, so the frequency was selected as "E." The importance and threat levels were both set to "1," the same as for row T310.

[0074] Regarding rows 313 and T314 of Table T3, since the railroad crossing has a road intersecting with the tracks, there is a possibility that pedestrians and automobiles may enter and be left behind after the railroad crossing alarm goes off. Therefore, the frequency for both pedestrians and automobiles was set to "A". The importance and threat level were set to the same as T39 for pedestrians and row T310 for automobiles.

[0075] For row 315 of Table T3, if there is a fence between stations, it is not easy for pedestrians to enter the track because they need to climb over the fence, so we determined that the probability of pedestrians entering between stations with fences is low, and set the frequency to "E." The importance and threat levels were both set to "2," the same as for T39.

[0076] The above frequency, importance, and threat level setting method is an example, and the selection results for frequency, importance, and threat level may be different from those in Table T3. Alternatively, in this embodiment, a route-specific risk matrix may be created based on the standard risk matrix, and if there is a deficiency in the route-specific risk matrix, information may be added, and the content of the standard risk matrix may be expanded based on the created route-specific risk matrix. Alternatively, in this embodiment, a route-specific risk matrix may be created for a specific route at first and provisionally registered as a standard risk matrix, and when applied to other routes, the provisionally registered standard risk matrix may be used as a basis for a risk matrix for other routes.

[0077] Fig. 10 shows a specific example of a countermeasure candidate matrix. The illustrated example shows a case where the distance is 240 to 2000 m, the distance between stations is selected as the section characteristic, no obstructions are selected as the lineside characteristic, the terrain is flat, and pedestrians are selected as the obstacles, and different countermeasures are applied to the speed limit in rows T79, T710, and T711.

[0078] In Table T7, row T71 contains the same information as the risk matrix described above. In addition to the information contained in the risk matrix, Table T7 contains detection distance T72, countermeasure candidate T73, countermeasure implementation section (countermeasure kilometre) T74, S risk level after countermeasure candidate implementation T75, A risk level T76, margin of error T77, and energy saving effect T78, all of which are quoted from the detection performance information 23.

[0079] The candidate countermeasures T73 show three levels of countermeasures, the first countermeasure Level.1 to the third countermeasure Level.3, shown in table T712 of FIG. 10. The first countermeasure Level.1 is a countermeasure for reducing damage caused by collision with a stationary object by taking into consideration no countermeasure or detection capability to some extent. The second countermeasure Level.2 is a countermeasure for avoiding collision with a stationary object by setting a speed limit that allows the vehicle to stop at the detection distance and the speed limit of the first countermeasure Level.1, which will be described later, which is smaller. The third countermeasure Level.3 is a countermeasure for not only avoiding collision with a stationary object but also reducing damage caused by collision with a jumping object by setting a speed limit that allows the vehicle to stop at a distance shorter than the detection distance and the speed limit of the first countermeasure Level.1, which is smaller.

[0080] Specifically, the speed limit corresponding to the first countermeasure Level 1 is set to the standard speed limit or to a speed limit at which the vehicle can stop at a value obtained by adding a first predetermined value α1 to the obstacle detection distance. In the case of the first countermeasure Level 1, since there is no guarantee that the vehicle can stop when a stationary object is detected, it may not be possible to avoid a collision with the stationary object, and since the vehicle 1 applies the brakes after detecting the stationary object, it is desirable to reduce the damage caused by a collision with the stationary object.

[0081] Specifically, the speed limit corresponding to the second countermeasure Level 2 is the smaller of the standard speed limit and the speed limit at which the vehicle can stop at the distance obtained by subtracting the second predetermined value α2 from the obstacle detection distance. The second predetermined value (parameter) α2 is 0 or more, and the second predetermined value α2=0 is the speed limit at which the vehicle can stop just at the detection distance. In this embodiment, the second predetermined value α2=0 is assumed for explanation, but the second predetermined value α2 does not have to be 0. Therefore, it is possible to apply the brakes after discovering a stationary object and avoid a collision with the stationary object.

[0082] Specifically, the speed limit corresponding to the third measure Level 3 is set to the smaller of the standard speed limit and the speed limit at which the vehicle can be stopped at a distance obtained by subtracting the third predetermined value α3 from the detection distance of the obstacle. The third predetermined value α3 is set so that the speed limit of the third measure Level 3 is equal to or lower than the speed limit of the second measure Level 2. According to the third measure Level 3, the vehicle can be stopped at a distance less than the detection distance, and therefore collision with a stationary object can be avoided. In addition, even if an obstacle appears within the detection distance, the vehicle can collide with the obstacle at a slower speed in the third measure Level 3 than in the second measure Level 2, so that at least damage to the vehicle can be reduced.

[0083] The countermeasure implementation section (countermeasure kilometres) T74 is a location range in which the speed limit is set according to the countermeasure candidate T73, and is defined by the location range (kilometres) of the section in T71, the detection distance T72 and the countermeasure candidate T73.

[0084] When the second countermeasure Level 2 or the third countermeasure Level 3 is required in a specific section defined by a combination of a certain section characteristic and line information, collision avoidance with an object present in the specific section, or collision avoidance and reduction of damage caused by an object jumping out are required. That is, the obstacle detection sensor 3 detects an object present at a nearby point closest to the vehicle 1 in the specific section. In the case of the second countermeasure Level 2, collision avoidance with a stationary object is required, and in the case of the third countermeasure Level 3, reduction of damage caused by a collision with an object jumping out to a nearby point is required. In the case of rows T79, T710, and T711 in Table T7, the specific section is 240 to 2000 m, and the nearby point is 240 m.

[0085] In order to avoid the collision or reduce the damage from the collision, the vehicle 1 needs to travel at a speed specified by the second measure Lv.2 or the third measure Lv.3 at a position a distance before the nearby point specified by the second measure Lv.2 or the third measure Lv.3. For example, when the second measure Lv.2 (avoidance of stationary objects) is required in a specific section, it becomes possible to avoid a collision with the object by having the obstacle detection sensor 3 detect an object that exists at a nearby point a detection distance before. In order to avoid a collision, it is necessary to set the speed at a point a detection distance before the nearby point so that the vehicle can stop at the detection distance.

[0086] Therefore, for row T710 of table T7, the countermeasure kilometre T74 is set to 240m (T71 kilometre minimum value) - 300m (detection distance T72 of the closest point to kilometre 240m) = -60m. Also, the countermeasure kilometre T74 corresponding to row T711 is set to 240m (T71 kilometre minimum value) - (300m (detection distance T72 of the closest point to kilometre 240m) - 50m (= α3)) = -10m.

[0087] Rows T75 and T76 show the S risk level and A risk level, respectively, after each countermeasure is implemented. Row T79 shows the evaluation results when the first countermeasure Level.1 is implemented, row T710 shows the evaluation results when the second countermeasure Level.2 is implemented, and row T711 shows the evaluation results when the third countermeasure Level.3 is implemented. As in row T79, the first countermeasure Level.1 cannot avoid collisions with pedestrians, so both evaluation results are △. On the other hand, as in row T710, the second countermeasure Level.2 can avoid collisions with stationary pedestrians, so both evaluation results are "○". Also, as in row T711, the third countermeasure Level.3 is evaluated as "◎" in consideration of the reduction in the frequency of collisions with protruding objects.

[0088] Row T77 is the margin time created in the corresponding kilometer section after each measure is implemented, and row T78 is the energy saving effect obtained by energy saving driving made possible by the margin time. The energy saving effect is defined as the energy reduction rate required for vehicle travel relative to the fastest pattern, for example.

[0089] The margin time indicates the time margin for the specified schedule when the fastest running is performed while observing the speed limit between stations. In this embodiment, the margin time T77 is a value obtained by subtracting the fastest running time between stations when a specific candidate countermeasure is adopted only in the kilometer section of interest, assuming that the countermeasure other than the kilometer section of interest is Level 1 (standard speed limit), from the running time required between stations.

[0090] Regarding the margin time T77 shown in Fig. 10, in the case of row T79, the entire section between station A and station B is at countermeasure level 1, and it is estimated that 20 seconds of margin time will be secured. On the other hand, row T710 is the case where countermeasure level 2 is used only in the corresponding kilometer section, and countermeasure level 1 is used in the other sections, and for example, it shows that a delay of 10 seconds has occurred because there is a section with poor visibility, which reduces the detection distance and reduces the speed limit determined by the detection distance. In row T711, the speed limit is even lower than in row T710, and a delay of 30 seconds has occurred.

[0091] As for the energy saving effect T78, since there is slack time in the case of row T79, it is possible to drive more energy-efficiently than the fastest pattern, and this indicates that there is a 1% energy reduction effect compared to the fastest pattern when energy-saving operation is performed. On the other hand, there is no slack time in the case of rows T710 and T711 due to delays, so there is no choice but to drive using the fastest pattern, and the energy saving effect T78 is 0%. The energy saving effect T78 is for reference only and is not essential in this embodiment.

[0092] 11 shows a specific example of a matrix after countermeasure consideration. Item T81 in table T8 is the same as T71 in countermeasure candidate matrix T7. The risk level and countermeasure consideration result integration unit 243 sets the result of selecting a countermeasure from countermeasure candidate T72 in countermeasure candidate matrix T7 as countermeasure T82, and sets S-level of risk T83, A-level of risk T84, and reason for selecting the countermeasure T85 for the selected countermeasure.

[0093] It is assumed that the selection of measures and the setting of the basis for selecting the measures are performed one by one by an operator by referring to Table T7. However, it is also possible to use a method for automatic selection by setting a rule such that, for example, from among measures with S risk level "△", A risk level "△", or a better level of risk than these, a measure with a slack time of a specified value, for example, 0 or more is selected.

[0094] A specific example of the countermeasure selection method will be described. For row T86 of table T8, in addition to avoiding collisions with stationary objects in the station premises, countermeasure level 3 was selected on the assumption that a train might rush out. For row T87, even with the first countermeasure level 1, both the S risk level and the A risk level were "○", and it was determined that the first countermeasure level 1 was acceptable. For row T88, if the second countermeasure level 2 was selected, the leeway time would be negative, and the conventional timetable could not be kept, and in addition, the driving method in the case of conventional manned driving without using obstacle detection sensors was the first countermeasure level 1, so the first countermeasure level 1 was selected.

[0095] In addition, a standard countermeasures after-consideration matrix may be created in advance, summarizing the scenes and countermeasures selection results, S risk level, A risk level, and countermeasures rationale. When examining a specific route, the route's scenes may be extracted, and elements of the standard countermeasures after-consideration matrix that match the route's scenes may be extracted to create a route-specific countermeasures after-consideration matrix.

[0096] In element T91 in table T9 shown in FIG. 11, instead of the kilometres in table T81, an ID is set to distinguish a combination of a travel section, lineside characteristics and obstacles.

[0097] Fig. 12 shows a specific example of the matrix after measures integration. In the example shown, measures T102 are set for section characteristics, line information, and station names for each travel section (start kilometres, end kilometres) as in item T101.

[0098] Countermeasure T102 is the most stringent countermeasure after sorting the countermeasure study results for each scene in the matrix by driving section (starting kilometer, ending kilometer). However, the order of the countermeasures is the strictest: first countermeasure Level 1, second countermeasure Level 2, third countermeasure Level 3.

[0099] For example, row T103 of table T10 selects the strictest measure among the measures for the scene set in the kilometer distance of 20 to 240 m in table T8 shown in Figure 11, i.e., rows T86 and T87.Since row T86 is the third measure Level 3 and row T87 is the first measure Level 1, the third measure Level 3 is selected.

[0100] 13 shows a specific example of the vehicle position where each countermeasure is implemented. Table T11 is a summary of the vehicle positions by the driving method map generating unit 244 described above based on the countermeasure integration matrix and the detection performance information 23.

[0101] The countermeasure start kilometres T116 in row T1110 of table T11 is the second countermeasure Level 2, so it is 2000m (start kilometres T111) - 250m (detection distance T114) = 1750m, and the countermeasure end kilometres T117 corresponding to row T118 is also 1750m. Also, row T1112 corresponds to the third countermeasure Level 3, so the countermeasure start kilometres T116 in row T1112 is 4000m (start kilometres) - (250m (detection distance T114) - 50m (= α3)) = 3800m. Also, the countermeasure end kilometres in row T1111 is also 3800m.

[0102] In this embodiment, the speed limit information 245 for each countermeasure start kilometer and countermeasure end kilometer T116, countermeasure end kilometer T117, countermeasure T115, detection performance information 23, and standard speed limit information 22 in table T11 obtained by the above procedure is used to calculate the speed limit information 245 for each countermeasure start kilometer and countermeasure end kilometer.

[0103] FIG. 14 shows a specific example of the countermeasure speed limit information 25. The countermeasure speed limit information 25 is information that summarizes countermeasures T123 and speed limits T124 for each countermeasure start kilometer T121 and countermeasure end kilometer T122, as in table T12. Since rows T126, T127, and T129 are countermeasure Level.1, the standard speed limit information 22 is adopted as the speed limit T124. Row T128 is countermeasure Level.2, and taking into consideration the detection distance, deceleration, etc., it is set to 75km / h. Rows T125 and T1210 are countermeasure Level.3, and since the detection distances are different, the countermeasure speed limit for row T125 is set to 85km / h, and for row T1210 it is set to 75km / h. The risk evaluation and countermeasure examination unit 24 described above executes the above-mentioned processing.

[0104] 15, the upper part shows a schematic diagram expressing the section characteristics and lineside characteristics divided by countermeasure sections, and the lower part shows a diagram visualizing the countermeasure speed limit at each point and the driving pattern calculated based on the countermeasure speed limit. The illustrated example shows the driving pattern created by the driving pattern generation unit 28.

[0105] Section G11 includes Station A, and section G15 includes Station B. Sections G11 and G15 are third countermeasure Level 3 sections. Sections G12 and G14 are first countermeasure Level 1 sections. Sections G12 and G14 are flat tracks without fences. Section G13 is a second countermeasure Level 2 section and includes a railroad crossing. Since section G13 is a second countermeasure Level 2 section, the start point of section G13 is set to a detection distance G110 before the start position of the railroad crossing. Since section G15 is a third countermeasure Level 3 section, the start point of section G15 is set to a position that is detection distance -α3 (α3 = 50m in this embodiment) before the start position of station B.

[0106] Next, in the diagram visualizing the driving pattern shown in the lower part of Fig. 15, the horizontal axis represents the position x (kilometers) and the vertical axis represents the speed v. The driving pattern generation unit 28 calculates countermeasure speed limit information G116 using the standard speed limit G113, the detection distance stoppable speed (second countermeasure Level 2 speed) G114, and the detection distance-α3 stoppable speed (countermeasure Level 3 speed) G115.

[0107] Furthermore, the travel pattern generation unit 28 calculates a travel pattern based on the countermeasure speed limit information G116 so as to satisfy the target travel time to the next station. For example, when the vehicle position information 27 is the stop position of Station A, the travel pattern generation unit 28 calculates a travel pattern that allows travel from the stop position of Station A to the stop position of Station B in the target travel time, as shown in Fig. 15. Note that the method of calculating the travel pattern may be any method that can satisfy the target travel time to the next station, and no specific method is specified in this embodiment.

[0108] According to the present embodiment as described above, an appropriate countermeasure level is selected by comparing the risk level, including the level of human injury and damage to the vehicle body in the event of a collision, with the leeway time, and by selectively using driving methods that ensure safe driving and leeway time in high-risk and low-risk sections, it is possible to ensure not only high safety and punctuality, but also leeway time.

[0109] In addition, in this embodiment, the starting positions of the second countermeasure Level 2 section and the third countermeasure Level 3 section are set a distance before the starting point of the section defined by the combination of section characteristics and line characteristics that should be the second countermeasure Level 2 and the third countermeasure Level 3, respectively, thereby making it possible to avoid collisions with stationary obstacles or reduce collision damage caused by obstacles rushing out, thereby making it possible to set a safe driving method.

[0110] Next, the operation of the driving pattern correction unit 210 will be described. The driving pattern correction unit 210 uses the current obstacle detection distance obtained by the detection performance calculation unit 29 and combines it with the detection performance information 23 to correct the detection distance used when calculating the speed limit for the second countermeasure Level 2 or the third countermeasure Level 3 section, and corrects the driving pattern generated by the driving pattern generation unit 28, taking into account the vehicle position information 27. In this way, the driving pattern correction unit 210 can reflect the current detection capability of the obstacle detection sensor 3 and improve driving safety.

[0111] Fig. 16 shows an example of a method for correcting a driving pattern. The method for correcting a driving pattern is performed by the driving pattern correction unit 210. First, as shown in the upper part of Fig. 16 (corresponding to G2 in the figure), the driving pattern correction unit 210 sets an estimated section G21 in the second countermeasure Level 1 section, and estimates the current obstacle detection capability of the obstacle detection sensor 3 in the estimated section G21.

[0112] The current detection capability of the obstacle detection sensor 3 is the detection capability of the obstacle detection sensor 3 at the point where the vehicle 1 is currently traveling, and is not the detection capability in the second countermeasure Level 2 section or the third countermeasure Level 3 section where the vehicle 1 will travel in the future. Therefore, in this embodiment, the driving pattern correction unit 210 uses the current detection capability of the obstacle detection sensor 3 to estimate the detection capability in the second countermeasure Level 2 section or the third countermeasure Level 3 section where the vehicle 1 will travel in the future.

[0113] When the detection performance expected for the section along which the vehicle will travel based on the current detection performance of the obstacle detection sensor 3 deteriorates at the start point of the section along which the vehicle will travel based on the current detection performance, the driving pattern correction unit 210 starts deceleration from the end position of the estimated section G21, and sets a position at which the vehicle can decelerate to the speed limit corresponding to the deteriorated detection performance by the start point of the section along which the vehicle will travel based on the current detection performance.

[0114] The method of estimating the detection capability according to this embodiment will be described below. For example, the driving pattern correction unit 210 calculates a deterioration coefficient by determining a first detection distance as the detection capability for the current position and dividing it by a second detection distance previously obtained at the same location. Furthermore, the driving pattern correction unit 210 can estimate the detection performance in the currently operating second countermeasure Level 2 section or third countermeasure Level 3 section by multiplying the detection distance in the previously obtained second countermeasure Level 2 section or third countermeasure Level 3 section by the deterioration coefficient.

[0115] 16, the difference x2-x1 between the start position x1 and end position x2 of the estimated section is, for example, the distance traveled until the detection distance of the obstacle is calculated by the above-mentioned detection performance calculation unit 29. In this case, for example, the end position x2-start position x1 can be found by dividing the time required for the detection distance of the obstacle to be calculated by the detection performance calculation unit 29 from the speed limit in the countermeasure level section corresponding to the inspection section.

[0116] The end position x2 of the estimated section is set to a position where, if the sensor detection distance decreases, the vehicle can decelerate to a speed dependent on the sensor detection distance specified in the second measure Level 2 or the third measure Level 3, by the start position of the second measure Level 2 section or the third measure Level 3 section, which is located immediately after the section to which the inspection section belongs.

[0117] In this embodiment, for example, a lower limit value for the detection distance when the detection performance of the obstacle detection sensor 3 has deteriorated is set in advance, and as shown in the upper part of Figure 16 (corresponding to G2 shown), in the second countermeasure Level.2 section, the vehicle is driven at a speed corresponding to the lower limit value of the detection distance, and a margin consideration pattern G22 is calculated in which the vehicle can decelerate to the lower limit value of the detection distance at the start position of the second countermeasure Level.2 section, and the intersection of the margin consideration pattern G22 with the driving pattern or countermeasure speed limit is designated as x2.

[0118] Next, the driving pattern correction unit 210 corrects the countermeasure speed limit and driving pattern based on the estimated current detection capability as follows. The diagram shown in the lower part of Fig. 16 (corresponding to G3 in the figure) shows an example of a driving pattern correction method. In the example shown, for the pre-correction countermeasure speed limit G31 and driving pattern G34, the countermeasure speed limit in the second countermeasure Level 2 section in the figure is corrected to a corrected countermeasure speed limit G33 calculated based on the detection distance estimated in the estimated section G21, and the corrected countermeasure speed limit is used to calculate the corrected driving pattern G34.

[0119] The driving pattern correction unit 210 as described above allows the vehicle 1 to drive in each countermeasure level section while taking into account the sensor detection distance that changes from moment to moment due to changes in illuminance, weather, etc., thereby enabling safer driving.

[0120] As described above, the driving pattern generation device 2 according to the present embodiment includes the detection performance information 23 indicating the detection performance of obstacles, the section characteristic map 21 indicating the type of driving section and the characteristics of surrounding objects, the standard speed limit information 22 regarding the standard speed limit when the vehicle travels, the vehicle position information 27 indicating the position of the vehicle 1, the standard driving curve information 26 indicating the driving mode set for the vehicle 1 to follow the timetable, and a risk evaluation and countermeasure examination unit 24 that uses the section characteristic map 21 and the countermeasure candidates for each of the multiple countermeasure candidates defined by the standard speed limit information 22 or the detection performance information 23 to calculate a risk level and a margin time, which are indexes considering the occurrence frequency and degree of both or either of human damage and vehicle damage in the event of a collision in the driving section, selects a countermeasure from the countermeasure candidates based on the risk level and the margin time, and calculates a countermeasure speed limit corresponding to the countermeasure, and a driving pattern generation unit 28 that calculates a driving pattern to the next station based on the countermeasure speed limit information, the standard driving curve information 26, and the vehicle position information 27. The driving pattern generation device 2 is mounted on the vehicle 1 as an example.

[0121] In this way, by calculating an optimal running pattern to the next station, not only can high safety and punctuality be ensured, but also slack time can be secured.

[0122] In this embodiment, the risk assessment and countermeasure examination unit 24 selects, as an example of a countermeasure, at least one of countermeasure Level.1, which sets the speed limit to the smaller of either the speed at which the vehicle can stop within a distance obtained by adding a first predetermined value to the obstacle detection distance by the obstacle detection sensor 3 or the standard speed limit, and countermeasure Level.2, which sets the speed limit to the smaller of either the speed at which the vehicle can stop within a distance obtained by subtracting a second predetermined value from the detection distance or the standard speed limit. In this way, a more preferable countermeasure can be adopted from among multiple countermeasures, and leeway time can be secured while ensuring high safety and punctuality.

[0123] In this embodiment, the risk assessment and countermeasure examination unit 24 may select, as a countermeasure, the first countermeasure Level.1, the second countermeasure Level.2, or the third countermeasure Level.3, which sets the speed limit to the smaller of the speed at which the vehicle can stop within the distance obtained by subtracting a third predetermined value from the detection distance and the standard speed limit. The speed limit of the third countermeasure Level.3 is equal to or lower than the speed limit of the second countermeasure Level.2. In this way, the speed limit of the third countermeasure Level.3, which is equal to or lower than the speed limit of the second countermeasure Level.2, is also adopted as a countermeasure, and it is possible to ensure high safety and punctuality while also ensuring a margin of time.

[0124] In this embodiment, the risk assessment and countermeasure consideration unit 24 includes a risk matrix generation unit 241 that uses the section characteristic map 21 to generate a risk matrix including risk levels for each traveling section based on the characteristics of the traveling section, the characteristics along the line, the vehicle threat level corresponding to the expected obstacles, the level of human damage, and the frequency of appearance of the obstacles; a risk measure consideration unit 242 that uses the risk matrix, the detection performance information 23, and the standard speed limit information 22 to generate a countermeasure candidate matrix that summarizes information including at least the risk reevaluation results and the margin time when the countermeasure candidate is implemented; a risk measure consideration result integration unit 243 that uses the results of selecting measures from the countermeasure candidate matrix based on the countermeasure candidate matrix to generate a post-countermeasure consideration matrix that summarizes the countermeasure consideration results for each traveling section; and a driving method map generation unit 244 that uses the post-countermeasure consideration matrix, the detection performance information 23, and the standard speed limit information 22 to output countermeasure speed limit information from the countermeasure start position and countermeasure end position of the countermeasure and the speed limit at the time of implementing the countermeasure. In this way, it is possible to ensure high safety and punctuality while also ensuring leeway time based on countermeasure speed limit information that sets the speed limit at the countermeasure start position and countermeasure end position when the countermeasure is implemented.

[0125] In this embodiment, the start point of the section where the countermeasure to determine the speed limit based on the detection performance is taken is a predetermined distance before the start point of the running section characteristics and lineside characteristics corresponding to the section where the countermeasure to determine the speed limit based on the detection performance is taken. By setting the start point of the section where the countermeasure is taken a predetermined distance before the start point, higher safety can be ensured.

[0126] In this embodiment, the predetermined distance is a distance at which the vehicle can be stopped at the speed limit used in the measure to determine the speed limit based on the detection performance. In this way, the predetermined distance allows the vehicle to be stopped at the speed limit used in the measure, thereby ensuring higher safety.

[0127] In this embodiment, the risk assessment and countermeasure examination unit 24 selects, for each travel section, from among the countermeasure candidates, a countermeasure that satisfies a predetermined level of risk and has a margin time equal to or greater than a predetermined value. In this way, by selecting the optimal countermeasure, it is possible to secure margin time while lowering risk.

[0128] The driving pattern generation device 2 according to this embodiment further includes a detection performance calculation unit 29 that calculates the current detection performance of the obstacle detection sensor 3 that detects an obstacle or a rail in front of the vehicle, and a driving pattern correction unit 210 that obtains an estimation result of the detection performance in the section along which the vehicle travels based on the current detection performance based on the current detection performance, and corrects the driving pattern output by the driving pattern generation unit 28 based on the estimation result of the current detection performance and vehicle position information 27. In this way, the driving pattern can be corrected according to the detection performance of the obstacle detection sensor 3, which changes from moment to moment while the vehicle 1 is traveling, thereby further improving safety.

[0129] In this embodiment, the estimated section is set before the section along which the vehicle travels based on the current detection performance, and the end position of the estimated section is a position where, if the detection performance expected for the section along which the vehicle travels based on the current detection performance is degraded at the start point of the section along which the vehicle travels based on the current detection performance, the vehicle 1 can start decelerating from the end position of the estimated section and decelerate to the speed limit corresponding to the degraded detection performance by the time it reaches the start point of the section along which the vehicle travels based on the current detection performance. In this way, even if the detection performance of the obstacle detection sensor 3 has degraded for some reason, the vehicle 1 can start decelerating from the end position of the estimated section and decelerate to the speed limit by the time it reaches the start point of the section along which the vehicle travels based on the current detection performance, thereby ensuring high safety.

[0130] In this embodiment, the driving pattern correction unit 210 calculates a deterioration coefficient by dividing a first detection distance, which is the detection capability of the obstacle detection sensor 3 at the current position, by a second detection distance, which is the detection capability of the obstacle detection sensor 3, previously acquired at the same position, and multiplies the detection distance of the section to be traveled by the deterioration coefficient based on the predefined detection performance to obtain an estimated result of the detection performance of the obstacle detection sensor 3. In this way, safer driving is possible by driving at each countermeasure level section, taking into account the detection distance of an obstacle by the obstacle detection sensor 3, which varies from moment to moment due to changes in illuminance, weather, etc.

[0131] (2) Second embodiment Since the second embodiment has the same configuration and operation as the first embodiment, in this embodiment, the same symbols are used for the similar configuration and operation and the explanation is omitted, and the following explanation will focus on the differences.

[0132] FIG. 17 is a diagram showing an example of the configuration of a vehicle 1a equipped with a driving pattern generation device 2b according to the second embodiment. In this embodiment, after safety is ensured in the section along which the vehicle travels based on the speed limit, the speed limit is relaxed to further ensure margin time. Specifically, unlike the driving pattern generation device 2 according to the first embodiment, the driving pattern generation device 2b according to the second embodiment includes a safety assurance determination unit 211. Also, the driving pattern generation unit 28a has almost the same function as the driving pattern generation unit 28 in the first embodiment, but generates a driving pattern using second countermeasure speed limit information output by the safety assurance determination unit 211 instead of the countermeasure speed limit information 25.

[0133] The safety assurance determination unit 211 has a function of determining whether or not, during driving, no objects are present in the entire section along which the vehicle should travel and safety is assured based on the detection performance information 23. The safety assurance determination unit 211 receives as input forward information acquired by the obstacle detection sensor 3, vehicle position information 27, and countermeasure speed limit information 25, and generates, for example, second countermeasure speed limit information relating to a second countermeasure speed limit that is higher than the above-mentioned speed limit, and outputs the second countermeasure speed limit information to the driving pattern generation unit 28a.

[0134] In Fig. 18, the upper part shows a schematic diagram in which the section characteristics and lineside characteristics are divided into countermeasure sections, and the lower part shows a diagram that visualizes the countermeasure speed limit at each point and the driving pattern calculated based on the countermeasure speed limit. The illustrated example shows the driving pattern created by the driving pattern generation unit 28a.

[0135] The illustrated example shows a specific example of a method for ensuring safety and a method for generating second countermeasure speed limit information by the safety ensuring determination unit 211. The vehicle 1 enters from a first countermeasure Level 1 section G41 into a second countermeasure Level 2 section G42, and then proceeds to a first countermeasure Level 1 section G43.

[0136] The range in which an object to be detected in the second countermeasure Level 2 section exists is within the section of the railroad crossing G45. When it is confirmed that no stationary object exists at the railroad crossing, the safety assurance determination unit 211 determines that safety is assured and relaxes the speed limit to the above-mentioned second countermeasure speed limit.

[0137] Specifically, as shown in Fig. 18, the safety assurance determination unit 211 determines that safety is not ensured over the entire crossing area even if there is no obstacle at the present time, because the safety assurance determination unit 211 cannot detect obstacles over the entire crossing area until the end of the obstacle detection distance G46 reaches the crossing's farthest point x5 while the vehicle 1 is traveling. On the other hand, when the end of the obstacle detection distance G46 reaches the crossing's farthest point x5 while the vehicle 1 is traveling and no obstacle is detected, the safety assurance determination unit 211 determines that safety is ensured because no obstacles exist over the entire crossing area.

[0138] When safety within the crossing range is ensured, the safety assurance determination unit 211 determines that no collision with a stationary object will occur in the crossing G45 section thereafter, and allows the speed of the first countermeasure Level.1, which has a lower countermeasure level, instead of the speed of the second countermeasure Level.2. Therefore, the safety assurance determination unit 211 sets the countermeasure speed limit information 25, which was originally increased to the standard speed limit at the farthest crossing point x5, to a second countermeasure speed limit G47, which increases the speed to the standard speed limit at a point before the farthest crossing point x5. Next, the driving pattern generation unit 28 generates a driving pattern G48 according to the second countermeasure speed limit G47.

[0139] In this embodiment, when the safety assurance determination unit 211 determines that no obstacle is detected by the obstacle detection sensor 3 by the time the vehicle reaches a position a detection distance before the end point of the section in which the vehicle travels based on the detection performance, the safety assurance determination unit 211 corrects the countermeasure speed limit to adopt the speed limit of the next section, and adopts a second countermeasure speed limit. Furthermore, the driving pattern generation unit 18 generates a driving pattern based on the second countermeasure speed limit.

[0140] By doing this, once safety has been ensured in a section where travel is based on a certain detection distance, such as the first countermeasure Level 2 section or the third countermeasure Level 3 section, it may be possible to quickly increase the speed to a higher standard speed limit, making it possible to secure further leeway while maintaining travel safety.

[0141] (3) Third embodiment Since the third embodiment has the same configuration and operation as the first embodiment, in this embodiment, the same symbols are used for the similar configuration and operation and the explanation is omitted, and the following explanation focuses on the differences.

[0142] FIG. 19 is a diagram showing an example of the configuration of a vehicle equipped with a risk assessment and countermeasures consideration unit 24a of the drive-pattern generation device in the third embodiment.

[0143] The margin time calculated by the risk countermeasure examining unit 242 in the first embodiment is the difference between the inter-station running time and the target running time when the countermeasure level is changed only in a specific section. The margin time calculated by adding up the margin times calculated by the running pattern generation method according to the first embodiment for all sections between stations is not necessarily the same as the margin time when the countermeasure level is changed in multiple sections.

[0144] In addition, the countermeasure candidate matrix generated by the risk countermeasure review unit 242 is an individual leeway time for each section, and it is desirable to be able to compare the leeway time between stations with the target running time to confirm whether the vehicle 1 can keep to the schedule.

[0145] Therefore, in the third embodiment, the risk assessment and countermeasures consideration unit 24 further includes a time calculation unit 246 and a risk countermeasure correction unit 247 as described below, in addition to the configuration of the first embodiment.

[0146] The time calculation unit 246 calculates the margin time between stations using the countermeasure speed limit information 25 generated by the driving method map generation unit 244. Specifically, the time calculation unit 246 uses the countermeasure speed limit information 25 generated by the driving method map generation unit 244 to calculate the difference between the target running time between stations and the running time at the fastest running time as the margin time after the countermeasure.

[0147] The risk countermeasure correction unit 247 judges whether or not to change the countermeasure level or the parameters used at specific countermeasure levels such as α1, α2, and α3 based on the margin time after the countermeasure is taken, and if it is determined that the margin time does not satisfy predetermined conditions and a change in the countermeasure level or parameters is necessary, it changes the countermeasure level or parameters, and re-calculates the revised countermeasure speed limit information using the risk countermeasure review unit 242, the risk countermeasure review result integration unit 243, and the driving method map generation unit 244, as described in the first embodiment.

[0148] On the other hand, if the risk countermeasure correction unit 247 determines that no change is necessary, it does not correct the countermeasure speed limit information 25 output by the driving style map generation unit 244, and outputs it as is as the countermeasure speed limit information 25.

[0149] In this embodiment, the criterion for determining whether or not the risk countermeasure correction unit 247 needs to change the countermeasure level or parameters is, for example, a method in which it is determined that the countermeasure level or parameter change is necessary when the leeway time after the countermeasure exceeds the target running time specified between stations and the train schedule cannot be maintained, but other methods may also be used.

[0150] Also, when it is judged that the risk countermeasure correction unit 247 needs to change the countermeasure level or the parameter, for example, the third countermeasure Level.3 section is relaxed to the second countermeasure Level.2 section to secure the margin time, or the parameter (corresponding to the above-mentioned "third predetermined value") α3=50m adopted in the third countermeasure Level.3 is changed to α3=20m to enable faster running, but other methods are also acceptable. Alternatively, when the margin time after the countermeasure is sufficiently secured, the countermeasure level of the specific section may be made stricter to increase the safety of running between stations.

[0151] In addition to the drive pattern generation device 2 according to the first embodiment, the drive pattern generation device according to this embodiment further includes a time calculation unit 246 that calculates the margin time between stations using the countermeasure speed limit information 25 described above, and a risk countermeasure correction unit 247 that changes the countermeasure between stations or the value (parameter) used in the countermeasure if the margin time between stations does not satisfy a predetermined condition, and recalculates the corrected countermeasure speed limit information by the risk countermeasure review unit 242, risk countermeasure review result integration unit 243, and drive method map generation unit 244 described above. In this way, the margin time to be secured can be calculated more accurately, and the countermeasure level according to the margin time can be reconsidered, thereby making it possible to secure safety and margin time more reliably.

[0152] (4) Other embodiments In the above embodiment, the type of vehicle 1 is not specifically described, but the present invention may be applied to vehicles such as streetcars, in addition to general rail vehicles. Also, the driving pattern generation devices 2 and 2b may be mounted on the vehicle 1 as in the above embodiment, or may be disposed outside the vehicle 1. [Industrial Applicability]

[0153] The present invention can be applied to a driving pattern generation device that generates a vehicle driving pattern that can ensure safety while also ensuring spare time, and to a vehicle. [Explanation of symbols]

[0154] 1,1a...vehicle, 2,2b...driving pattern generation device, 3...obstacle detection sensor, 21...section characteristic map, 22...standard speed limit information, 23...detection performance information, 24,24a...risk assessment and countermeasures consideration unit, 25...countermeasures speed limit information, 26...standard driving curve information, 27...vehicle position information, 28...driving pattern generation unit, 29...detection performance calculation unit, 210...driving pattern correction unit, 241...risk matrix generation unit, 242...risk countermeasures consideration unit, 243...risk countermeasures consideration result integration unit, 244...driving method map generation unit.

Claims

1. Detection performance information indicating the detection performance of an obstacle; A section characteristic map indicating a type of a travel section and characteristics of surrounding objects; standard speed limit information regarding the standard speed limit at which the vehicle is traveling; Vehicle position information indicating a position of the vehicle; Standard driving curve information representing a driving mode set for the vehicle to keep to a timetable; a risk assessment and countermeasure examination unit that uses the section characteristic map and the countermeasure candidates for each of a plurality of countermeasure candidates defined by the standard speed limit information or the detection performance information to determine a risk level and a margin of error, which are indexes taking into consideration the frequency of occurrence and severity of both or either of human damage and vehicle damage in the event of a collision in the traveling section, and selects a countermeasure from the countermeasure candidates based on the risk level and the margin of error, and calculates a countermeasure speed limit corresponding to the countermeasure; a travel pattern generation unit that calculates a travel pattern to a next station based on the countermeasure speed limit information related to the countermeasure speed limit, the standard running curve information, and the vehicle position information; A driving pattern generating device comprising:

2. The risk assessment and countermeasures examination unit comprises: As the countermeasure, at least Select one of a first measure in which the speed limit is set to the smaller of a speed at which the vehicle can stop within a distance obtained by adding a first predetermined value to the obstacle detection distance and the standard speed limit, and a second measure in which the speed limit is set to the smaller of a speed at which the vehicle can stop within a distance obtained by subtracting a second predetermined value from the obstacle detection distance and the standard speed limit.

2. The drive pattern generating device according to claim 1 .

3. The risk assessment and countermeasures examination unit comprises: As the countermeasure, the first countermeasure, the second countermeasure, or select a third measure that sets the speed limit to the smaller of the speed at which the vehicle can stop within a distance obtained by subtracting a third predetermined value from the detection distance and the standard speed limit; The speed limit of the third measure is equal to or less than the speed limit of the second measure.

3. The drive pattern generating device according to claim 2.

4. The risk assessment and countermeasures examination unit comprises: a risk matrix generating unit that uses the section characteristic map to generate a risk matrix including the risk for each traveling section based on the traveling section characteristics, the railway line characteristics, the vehicle threat level corresponding to the expected obstacles, the level of human damage, and the frequency of appearance of the obstacles; and a risk countermeasure examination unit that uses the risk matrix, the detection performance information, and the standard speed limit information to generate a countermeasure candidate matrix that summarizes information including at least a risk reevaluation result and the margin time in a case where the countermeasure candidate is implemented; a risk level countermeasure examination result integration unit that generates a countermeasure examination post-examination matrix by using a result of selecting countermeasures from the countermeasure candidate matrix based on the countermeasure candidate matrix, the countermeasures being summarized as countermeasure examination results for each travel section; a driving method map generating unit that uses the countermeasure consideration matrix, the detection performance information, and the standard speed limit information to output the countermeasure speed limit information from the countermeasure start position and countermeasure end position of the countermeasure and the speed limit when the countermeasure is implemented; 2. The drive pattern generating device according to claim 1, further comprising:

5. A start point of the section where the measure for determining the speed limit based on the detection performance is performed is a predetermined distance before a start point of the running section characteristics and the lineside characteristics corresponding to the section where the measure for determining the speed limit based on the detection performance is performed.

2. The drive pattern generating device according to claim 1 .

6. The predetermined distance is used in the measure for determining the speed limit based on the detection performance. The distance at which a vehicle can stop at the speed limit 6. The drive pattern generating device according to claim 5,

7. The risk assessment and countermeasures examination unit comprises: For each of the travel sections, a countermeasure in which the degree of risk meets a predetermined level and the margin time is equal to or greater than a predetermined value is selected from the countermeasure candidates.

2. The drive pattern generating device according to claim 1 .

8. a detection performance calculation unit that calculates a current detection performance of an obstacle detection sensor that detects an obstacle or a front rail in front of the vehicle; a driving pattern correction unit that obtains an estimation result of detection performance in a section along which the vehicle is traveling based on the current detection performance based on the current detection performance, and corrects the driving pattern output by the driving pattern generation unit based on the estimation result of the detection performance and the vehicle position information; The drive pattern generating device according to claim 1, further comprising:

9. The driving pattern correction unit is setting an estimated section for estimating a current detection capability before a section along which the vehicle will travel based on the current detection performance; As the end position of the estimated section, When the detection performance estimated for the section along which the vehicle travels based on the current detection performance is degraded at the start point of the section along which the vehicle travels based on the current detection performance, deceleration is started from the end position of the estimated section, and a position is set at which the vehicle can decelerate to the speed limit corresponding to the degraded detection performance by the start point of the section along which the vehicle travels based on the current detection performance.

9. The drive pattern generating device according to claim 8.

10. The driving pattern correction unit is A deterioration coefficient is calculated by dividing a first detection distance, which is the detection capability of the obstacle detection sensor at the current position, by a second detection distance, which is the detection capability of the obstacle detection sensor, previously acquired at the same position, and an estimated result of the detection capability of the obstacle detection sensor is obtained by multiplying the detection distance of a section to be traveled by the deterioration coefficient based on a detection capability defined in advance.

10. The drive pattern generating device according to claim 8 or 9.

11. a safety assurance determination unit that, when an obstacle is not detected in a section in which the vehicle travels based on the detection performance until the vehicle reaches a position a detection distance before an end point of the section in which the vehicle travels based on the detection performance, thereafter corrects the countermeasure speed limit to adopt a second countermeasure speed limit so as to adopt the speed limit of a next section; The driving pattern generation unit is Generate a driving pattern based on the second countermeasure speed limit 2. The drive pattern generating device according to claim 1 .

12. A time calculation unit that calculates a margin time between stations using the countermeasure speed limit information; and a risk measure correction unit that changes the measures between stations or values ​​used in the measures when the margin time between stations does not satisfy a predetermined condition, and recalculates corrected countermeasure speed limit information by the risk measure review unit, the risk measure review result integration unit, and the driving method map generation unit.

5. The drive pattern generating device according to claim 4.

13. Detection performance information indicating the detection performance of an obstacle; A section characteristic map indicating a type of a travel section and characteristics of surrounding objects; standard speed limit information regarding the standard speed limit at which the vehicle is traveling; Vehicle position information indicating a position of the vehicle; Standard driving curve information representing a driving mode set for the vehicle to keep to a timetable; a risk assessment and countermeasure examination unit that uses the section characteristic map and the countermeasure candidates for each of a plurality of countermeasure candidates defined by the standard speed limit information or the detection performance information to determine a risk level and a margin of error, which are indexes taking into consideration the frequency of occurrence and severity of both or either of human damage and vehicle damage in the event of a collision in the traveling section, and selects a countermeasure from the countermeasure candidates based on the risk level and the margin of error, and calculates a countermeasure speed limit corresponding to the countermeasure; a travel pattern generation unit that calculates a travel pattern to a next station based on the countermeasure speed limit information related to the countermeasure speed limit, the standard running curve information, and the vehicle position information; The driving pattern generating device is equipped with A vehicle characterized by:

14. a risk evaluation and countermeasure consideration step in which a risk evaluation and countermeasure consideration unit of the driving pattern generation device uses a section characteristic map representing the type of driving section and the characteristics of surrounding objects and the countermeasure candidates to determine a risk, which is an index considering the occurrence frequency and degree of both or either of human damage and vehicle damage in the event of a collision in the driving section, and a margin time for each of a plurality of countermeasure candidates defined by standard speed limit information related to the standard speed limit when the vehicle is traveling or detection performance information representing the detection performance of an obstacle, selects a countermeasure from the countermeasure candidates based on the risk and the margin time, and calculates the countermeasure speed limit corresponding to the countermeasure; a travel pattern generation step in which a travel pattern generation unit of the travel pattern generation device calculates a travel pattern to a next station based on countermeasure speed limit information related to the countermeasure speed limit, standard driving curve information representing a travel mode set so that the vehicle follows a timetable, and vehicle position information representing a position of the vehicle; A driving pattern generating method comprising the steps of:

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